(Photo credit: Argonne National Laboratory.)
A recent survey of insurance professionals by Boston-based research and advisory firm SMA found that all life and annuity (L&A) carriers are increasing spending on business intelligence (BI) and analytics. The report on the survey, “Data and Analytics in Insurance: L&A Insurer Strategic Priorities and Operational Plans Through 2016,” found that the area of risk (actuarial, new product development and underwriting) had the highest level of analytics use among carriers, and that insurers were increasingly focusing their BI/analytics investments on profitability and customer insight.
Mark Breading, Partner, SMA.
“The golden era of analytics is upon us, and most L&A insurers are aggressively investing,” comments Mark Breading, partner, SMA, and co-author of the study. “The winners will be those that focus on organizing data, building analytics talent, and creating a culture of innovation that enables experimentation.”
The survey found that 77 percent of insurers were focused on profitability through assessment of profit levers by product, channel, territory and other factors, and that the remaining 23 percent were either currently implementing new systems or planned to do so by 2016.
Risk was the highest area of analytics activity among SMA’s respondents, who reported new initiatives to create rules engines and predictive tools. But L&A companies’ customer-related (customer insights, marketing, distribution) analytics efforts are gaining momentum, according to SMA. For example, 50 percent of L&A insurers currently use analytics for customer relationship management (CRM) while 49 percent plan to implement new capabilities by 2016.
Insurers’ increased investment in analytics is significantly driven by the quest to acquire new customers, according to SMA’s Breading. “Life insurers are thinking about redesigning the whole customer acquisition process,” he says. “That involves the new business sales and underwriting process, the recruitment and training of agents and the management of distribution networks – analytics underpins all of that.”
Insurers are striving to better understand lifetime customer value as well as producer appetite and profitability, according to Breading. “Carriers are asking what their producers do well, how they can better serve them, and how they can refine and rethink their segmentation,” he says. “Those investigations drive others, for example about which products for which customer segments.”
Insurers’ activity has been triggered by the availability of an increasing variety of data sources and the proliferation of better tools to process data, Breading suggests. More L&A carriers are working on predictive analytics and models, and some of the larger firms are experimenting with cognitive computing, he says.
Data/text mining projects account for the greater part of carriers’ advanced analytics activities, for example, analysis of new business communications between producers, new business professionals, and underwriters (e.g. e-mails or notes embedded in core systems). Another example is mining contact center logs to identify cross-sell opportunities or customers at risk of policy lapse, according to the SMA report.
In their heightened investment in analytics, L&A carriers are catching up with the P&C industry to an extent by bringing in capabilities, exploring new data sources and building up their internal talent, according to Breading. “The opportunity is huge if they can build up these capabilities and at an enterprise level; this is an enterprise-level function, not something you embed in IT,” he cautions. “The goal is to be able to drive strategies across the business.”
Investment in BI/analytics and use of expanded data sources will bring carriers closer to mastery of data-driven business, which is emerging as a vital competency, according to Denise Garth, partner at SMA and co-author of the report with Breading. “This is mandatory in today’s shifting competitive landscape and digital economy,” she comments.
“The big winners will be those companies that know what data to pull I, how to analyze it and how to take action on it,” predicts Breading.